What would they benefit from this?
Why do they have anything to do with AI at all?
Why do they have anything to do with AI at all?
All of that would be future product development, but I suspect this addition is for exactly that reason: so they can begin to prepare the ground for later development, not because they're going to immediately roll this out tomorrow.
See the terms:
> Sentry may use Usage Data and Service Data for analytics and product development (including to train or improve AI Features and generate Outputs). Sentry will not disclose Usage Data or Outputs externally, unless they have been de-identified so that they do not individually identify Customer, its Users or any other person and are aggregated with data across Sentry’s other customers.
That is incorrect, the data is exclusively used to provide services to customers. The blog post is quite specific about the intended use.
> Sentry will not disclose Usage Data or Outputs externally, unless they have been de-identified so that they do not individually identify Customer, its Users or any other person and are aggregated with data across Sentry’s other customers.
You can write whatever you want in a blog post. It’s the legal terms and what’s in the contract that matters and presumably shows intent.
In this case they are clearly planning to show or sell de-identified data as it’s in their terms and conditions explicitly. What is being said in the blog and what the company is giving themselves a license to do are not the same.
If you have a "can't access key 'foo' of undefined" error, adding a check if the object is undefined or not is not a fix. It's simply silencing the error.
The bug might be way, way down in the stack, maybe even in the backend or somewhere else in the client that made the backend store invalid data my mistake.
I highly doubt that the current breed of models are capable of this.
It is certainly not enough for every case, but it is enough (and the models are smart enough) to be useful.
It really isn't.
I just did a test with a random TypeScript file with 400 lines of code which translates to almost exactly 3000 tokens in the GPT-4 token counter app.
This means that we are talking about being capable to analyse a maximum of 43 small / medium sized files.
Each analysis will also cost $1.28 without any additional intermediary costs.
Today one of the largest challenge with Sentry at scale is that every error looks the same. If statements only get you that far. One of the ways in which we want to improve this is to use issue interaction and the event's content to predict the severity of an issue.
The second case is a version of suggested fix that uses your code to suggest actual fixes to your code. In this case the data never crosses your organization's boundary and is private to yourself.